Technology Management for Accelerated Recovery during COVID-19
SEISENSE Journal of Management , Volume 3, pp 33-53; doi:10.33215/sjom.v3i5.445
Abstract: Objective- The research looks forward to extracting strategies for accelerated recovery during the ongoing Covid-19 pandemic. Design - Research design considers quantitative methodology and evaluates significant factors from 170 countries to deploy supervised and unsupervised Machine Learning techniques to generate non-trivial predictions. Findings - Findings presented by the research reflect on data-driven observation applicable at the macro level and provide healthcare-oriented insights for governing authorities. Policy Implications - Research provides interpretability of Machine Learning models regarding several aspects of the pandemic that can be leveraged for optimizing treatment protocols. Originality - Research makes use of curated near-time data to identify significant correlations keeping emerging economies at the center stage. Considering the current state of clinical trial research reflects on parallel non-clinical strategies to co-exist with the Coronavirus.
Keywords: Treatment / models / machine learning / pandemic / optimizing / Considers / Accelerated Recovery / COVID
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